Data Engineer Coach

FIND | Creating Futures
Sheffield
3 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer - Defence

Data Engineer

Lead Data Engineer: Architect Scalable Data Pipelines

Lead Data Engineer

Data Engineering Coach - Remote working


Are you a technically strong Data Engineer who loves mentoring others?

Do you want to help shape the next generation of Data Engineers

On behalf of a scaling Technology Training provider, we’re looking for a Data Engineering Coach to train and coach Data Engineering apprentices


You’ll use your technical expertise to deliver training, provide hands-on coaching, and help learners build the real-world skills and confidence they need to succeed in their careers.

What you’ll be doing:

  • Coaching & training Data Engineering apprentices on 12-week dedicated Data Engineering training programmes.
  • Deliver hands-on, interactive group training to the apprentices, from foundation to more advanced Data Engineering topics & practices
  • Provide further 1-to-1 & small group coaching to the apprentices
  • Act as the SME for the 12-week Data Engineering programme, ensuring it’s up to date with all of the latest tools, trends & practices within Data Engineering.
  • Running interactive workshops, kick-off sessions, and wrap-ups/assessment, while guiding learners through self-led content.
  • Being client facing – discussing technical skills gaps & training requirements with this companies client base.


About you:

We’re NOT looking for an Academic – we’re looking for a technically solid Data Engineer who enjoys coaching & mentoring others, and knowledge sharing.

You’ll bring:

  • Strong industry experience within Data Engineering & Cloud
  • Experience with these tools, or familiar: Python, SQL, Kafka, Airflow, Azure, AWS
  • DevOps experience would be a plus (desirable)
  • Formal OR informal Training or Coaching experience (Coach / Mentor / Trainer / Instructor / Tutor / Lecturer etc.)
  • Resilience and openness – comfortable in a fast-moving, start-up or scale-up style environment


This is a remote working position, meaning you can be based from anywhere within the UK.

Salary is £65,000 (negotiable)


Please reach out for more info:

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers Jobs

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

Jobs

How to Write a Data Science Job Ad That Attracts the Right People

Data science plays a critical role in how organisations across the UK make decisions, build products and gain competitive advantage. From forecasting and personalisation to risk modelling and experimentation, data scientists help translate data into insight and action. Yet many employers struggle to attract the right data science candidates. Job adverts often generate high volumes of applications, but few applicants have the mix of analytical skill, business understanding and communication ability the role actually requires. At the same time, experienced data scientists skip over adverts that feel vague, inflated or misaligned with real data science work. In most cases, the issue is not a lack of talent — it is the quality and clarity of the job advert. Data scientists are analytical, sceptical of hype and highly selective. A poorly written job ad signals unclear expectations and immature data practices. A well-written one signals credibility, focus and serious intent. This guide explains how to write a data science job ad that attracts the right people, improves applicant quality and positions your organisation as a strong data employer.

Education Jobs

Maths for Data Science Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are applying for data science jobs in the UK, the maths can feel like a moving target. Job descriptions say “strong statistical knowledge” or “solid ML fundamentals” but they rarely tell you which topics you will actually use day to day. Here’s the truth: most UK data science roles do not require advanced pure maths. What they do require is confidence with a tight set of practical topics that come up repeatedly in modelling, experimentation, forecasting, evaluation, stakeholder comms & decision-making. This guide focuses on the only maths most data scientists keep using: Statistics for decision making (confidence intervals, hypothesis tests, power, uncertainty) Probability for real-world data (base rates, noise, sampling, Bayesian intuition) Linear algebra essentials (vectors, matrices, projections, PCA intuition) Calculus & gradients (enough to understand optimisation & backprop) Optimisation & model evaluation (loss functions, cross-validation, metrics, thresholds) You’ll also get a 6-week plan, portfolio projects & a resources section you can follow without getting pulled into unnecessary theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.